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FLUX.1 Kontext

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Re: FLUX.1 Kontext

#61

Post by throwaway314155 »

pkkkzip wrote: post #57
amazingamazing wrote: post #11

Don’t understand the remove from face example. Without other pictures showing the persons face, it’s just using some stereotypical image, no?

They chosen Asian traits that Western beauty standards fetishize that in Asia wouldn't be taken serious at all. I notice American text2image models tend to generate less attractive and more darker skinned humans where as Chinese text2image generate attractive and more light skinned humans. I think this is another area where Chinese AI models shine.

> notice American text2image models tend to generate less attractive and more darker skinned humans where as Chinese text2image generate attractive and more light skinned humans

This seems entirely subjective to me.

Re: FLUX.1 Kontext

#62

Post by meowface »

cuuupid wrote: post #43
minimaxir wrote: post #21

Currently am testing this out (using the Replicate endpoint: https://replicate.com/black-forest-labs/flux-kontext-pro ). Replicate also hosts "apps" with examples using FLUX Kontext for some common use cases of image editing: https://replicate.com/flux-kontext-apps It's pretty good: quality of the generated images is similar to that of GPT-4o image generation if you were using it for simple image-to-image generations…

Honestly love Replicate for always being up to date. It’s amazing that not only do we live in a time of rapid AI advancement, but that every new research grade model is immediately available via API and can be used in prod, at scale, no questions asked. Something to be said about distributors like Replicate etc that are adding an exponent to the impact of these model releases

I have no affiliation with either company but from using both a bunch as a customer: Replicate has a competitor at https://fal.ai/models and FAL's generation speed is consistently faster across every model I've tried. They have some sub-100 ms image gen models, too.

Replicate has a much bigger model selection. But for every model that's on both, FAL is pretty much "Replicate but faster". I believe pricing is pretty similar.

Re: FLUX.1 Kontext

#63

Post by [deleted] »

vunderba wrote: post #41

I'm debating whether to add the FLUX Kontext model to my GenAI image comparison site. The Max variant of the model definitely scores higher in prompt adherence nearly doubling Flux 1.dev score but still falling short of OpenAI's gpt-image-1 which (visual fidelity aside) is sitting at the top of the leaderboard. I liked keeping Flux 1.D around just to have a nice baseline for local GenAI capabilities. https://genai-sh…

[deleted]

Re: FLUX.1 Kontext

#64

Post by mdp2021 »

Is input restricted to a single image? If you could use more images as input, you could do prompts like "Place the item in image A inside image B" (e.g. "put the character of image A in the scenery of image B"), etc.

Re: FLUX.1 Kontext

#65

Post by carlosdp »

mdp2021 wrote: post #64

Is input restricted to a single image? If you could use more images as input, you could do prompts like "Place the item in image A inside image B" (e.g. "put the character of image A in the scenery of image B"), etc.

There's an experimental "multi" mode you can input multiple images to

Re: FLUX.1 Kontext

#66

Post by liuliu »

krackers wrote: post #56
liuliu wrote: post #22

Earlier quoted context omitted.

Seems implementation is straightforward (very similar to everyone else, HiDream-E1, ICEdit, DreamO etc.), the magic is on data curation (which details are lightly shared).

I haven't been following image generation models closely, at a high level is this new Flux model still diffusion based, or have they moved to block autoregressive (possibly with diffusion for upscaling) similar to 4o?

Diffusion based. There is no point to move to auto-regressive if you are not also training a multimodality LLM, which these companies are not doing that.

Re: FLUX.1 Kontext

#67

Post by echelon »

mdp2021 wrote: post #64

Is input restricted to a single image? If you could use more images as input, you could do prompts like "Place the item in image A inside image B" (e.g. "put the character of image A in the scenery of image B"), etc.

Fal has the multi image interface to test against. (Replicate might as well, I haven't checked yet.)

THIS MODEL ROCKS!

It's no gpt-image-1, but it's ridiculously close.

There isn't going to be a moat in images or video. I was so worried Google and OpenAI would win creative forever. Not so. Anyone can build these.

Re: FLUX.1 Kontext

#68

Post by doctorpangloss »

vunderba wrote: post #45

Some of these samples are rather cherry picked. Has anyone actually tried the professional headshot app of the "Kontext Apps"? https://replicate.com/flux-kontext-apps I've thrown half a dozen pictures of myself at it and it just completely replaced me with somebody else. To be fair, the final headshot does look very professional.

Nobody has solved the scientific problem of identity preservation for faces in one shot. Nobody has even solved hands.

Re: FLUX.1 Kontext

#70

Post by dagaci »

ttoinou wrote: post #39
throwaway675117 wrote: post #25

Earlier quoted context omitted.

Just use https://github.com/bghira/SimpleTuner I was able to run this script to train a Lora myself without spending any time learning the underlying python libraries.

Well thank you I will test that

SimpleTuner is dependant on Microsoft's DeepSpeed which doesnt work on Windows :)

So you probably better off using Ai-ToolKit https://github.com/ostris/ai-toolkit

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